Experimental and Modeling Study of the Effects of CO2 Injection on Gas/Condensate Recovery and CO2 Storage in Gas-Condensate Reservoirs
Bibliographic record
Abstract
Abstract The mixing/interaction between injected gas and remaining reservoir fluid is yet to be extensively understood and the inability to optimize the recovery process has led to limited pilot trials. Therefore, adequate phase and flow behavior analyses and modeling are necessary to better evaluate reservoir performance under CO2 injection to make an informed decision. In this work, the phase behavior, and the minimum miscible pressure (MMP) have been experimentally conducted to determine the level of CO2/gas-condensate interaction, including condensing/mixing/vaporizing mechanisms. Moreover, the unsteady-state flow tests were conducted to study flowing characteristics and performance. Based on these studies, the CO2 injection numerical model was constructed using a component model reservoir simulator (GEM) to simulate the effects of injection rate, injection pressure, and injection volume on gas/condensate recovery and CO2 storage. Finally, the stability of CO2 storage was evaluated using numerical simulation of the reservoir. The results were analyzed and found that the phenomenon of "critical opalescence" occurred when a certain proportion of CO2 was injected into the residual condensate oil and gas system, which meant that CO2 and condensate were mixed as one phase. Factors such as injection pressure, injection rate, and injection volume have a very important influence on the degree of condensate recovery. Only considering the influence of single factor conditions, the higher the injection pressure or gas injection volume or injection rate, the higher the degree of condensate recovery and the greater the potential of CO2 storage. However, based on comprehensive consideration of oil displacement rate and gas channelization, reasonable gas injection speed, injection volume, and injection pressure were finally optimized and screened out as 7000 m3 /day, 0.43 HCPV, and 32 MPa, respectively. The formation pressure was almost constant from 80 years to 130 years, which indicated that CO2 can be deposited stably. The study bridges the gap between the extent of CO2/gas-condensate interaction at pressures below the dew point pressure and conflicting reports on this trend. This paper also provides a better knowledge of the governing mechanisms during CO2 injection, which are required for designing suitable CO2 flooding injection for reservoir engineering applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".